ADC Background

Work on EViP technology was initiated by ADC’s founder, Dr. Tuan A Duong, while he was working at NASA’s Jet Propulsion Laboratory, in one of three frontier neural network teams in the United States (including AT&T Bell Labs and Bellcore) in 1984.  

Some of the relevant projects Dr. Duong researched and developed during his time at JPL include:

* Real-Time Mars Landing Site Identification  based on real-time color segmentation and adaptation, supported by Self-Evolving Neural Network Architecture namely Cascade Error Projection, to survey and identify a safe and productive landing site in real-time;

* Self-Evolving Neural Network Architecture Supervised Learning algorithm to identify Amino Acid building blocks for Life Detection Mission.

* Space Invariant Independent Component Analysis (SPICA) for recovering the original odorant sources from unknown mixtures for ENose (a multi-element chemical sensor) in an open unknown environment (Caltech patent).

* Introductory Extended Visual Pathway Data Flow, a technology which has now been fully developed at ADC (Caltech patent).

* Cognitive Computing Architecture that enables a general-purpose neural processor chip to be equipped with a compiler, making low power, compactness, and real-time adaptive operation available in a single package.  This set a cornerstone for intelligent perception and recognition in hardware implementation (Caltech patent).

* Others.

With his 12 patents with NASA or Caltech Assignee, 3 patents with ADC Assignee, and nine of them are neural networks related technology.

These technologies have provided the foundation for the technologies ADC has now brought to fruition.  NASA/JPL-Caltech provided generous support and an excellent environment for doing this preliminary research.  Involvement through licensing and other arrangements continues to be a key to ADC’s success.

Our Technology

At Adaptive Computation LLC, Dr. Tuan A Duong invented the Extended Visual Pathway (EViP) approach as an unsupervised learning approach to integrate a saccadic eye movement emulator with a bio-inspired visual processing pathway to enable the detection and recognition of generic full/partial/low resolution/ sketched/degraded objects in open and ambiguous environments.  This basic technology is protected by US and international patents.

He also invented a new learning architecture to enable the machine to self-learn new objects autonomously and additively in a sequential manner when the objects arrive and appear at different times. Hence the cognitive and perceptive capability can be equipped for machine intelligence. 

Based on this proven approach, ADC is designing a revolutionary product:  a hybrid high-speed correlator/neural network EViP chip, 5x5mm2 in size and weighing a few grams, and accommodating Tera-ops/sec processing speeds with less than 2 pjoules/operation. As an embedded search tool, this will give handheld devices on-board processing capabilities that outperform even the sophisticated server-based systems of today.  A provisional patent has been filed.

Extended Visual Pathway (EViP)

EViP consists of a saccadic eye movement emulator and visual pathway filters and visual cortex.


Complete Autonomous and Adaptive Learning System (CAALS)


Reconfigurable Intelligent Search Engine (RISE)

Reconfigurable Intelligent Search Engine (RISE) is an implementation of EViP via Real-Time Extraction Engine (ReTEE) and architecture.

This is an illustration only.